Genome wide association and genomic selection to speed up genetic improvement for meat quality in Hanwoo

Transcription

1 Genome wide association and genomic selection to speed up genetic improvement for meat quality in Hanwoo Seung Hwan Lee, PhD Hanwoo Experiment Station, National Institute of Animal Science, RDA 1

2 National Institute of Animal Science, RDA Department of Animal Biotechnology & Environment Seoul Pyungchang Hanwoo Exp. Station Animal Genetic Resources Station Suwon Seongwhan Namwon Department of Animal Resources Development Jeju Subtropical Anim Exp Station 2

3 Genomic Networking in NIAS, RDA Genetic Improvement National Breeding Program Planning, strategy of breeding program Development of Breeding tools Optimization of Breeding program Delivery Genomics into Breeding Animal Genome & Bioinformatics Genome project for Livestock Bioinformatics Development of Genomic tools QTL, GWAS, GS model Hanwoo Experiment Station Evaluation of GS model Validation of QTL, GWAS etc Line breeding 3

4 Statistics for Hanwoo Industry Location farm % Head % Whole country 165,420 3,034,812 Seoul Busan , Daegu 1, , Incheon , GwangJu , Daejeon , Ulsan 1, ,927 1 Gyeonggi 6, , Gangwon 12, , Chungbuk 10, , Chungnam 21, , Jeonbuk 15, , Jeonnam 33, , Gyeongbuk 35, , Gyeongnam 25, , Jeju , million head (total) 1.3 million head (Cow) 165,420 farm Incheon Gyeonggi Chungnam Seoul Daejeon Jeonbuk Gwangju Jeonnam Jeju-do Chungbuk Gangwon Gyeongbuk Daegu Ulsan Gyeongnam Busan 4

5 Hanwoo Supply Chain Government Funding Seed Stock MIFAFF -> NIAS + NACF (1,000 cows) Breeding farms (Registered 75 farms with 100 cows, total 8,000 cows) Performance and Progeny testing Selection of bulls, selling a semen straw by NACF Multipliers Feedlot sector Production of calves Feedlot farms (average 16.5 heads) some of them are large scale but most of all are very small scale Beef supply chain Beef Grading system Beef Palatability system MIFAFF: Ministry for food, agriculture, Forestry and Fishery NACF: National Agricultural Cooperative Federation NIAS: National Institute of Animal Science KAPE : Korea Institute for Animal Products Quality Evaluation AIAK : Korea Animal Improvement Association 5

6 Bull selection in Seed Stock Sector Elite Bull Elite Cows NACF (1,000 cows) Breeding farms (8,000 cows) Young Bulls (700 heads) Purchasing from breeding farms 28 Months Candidate Bulls(55 heads) Performance Testing at 6 and 12Months Growth trait Progeny testing Hanwoo farms (2,500 head) Breeding farms (800 heads) 750 heads 38 Months Total 5.5 years NACF (400 heads) Breeding farms (100 heads) KPN Bulls (20 heads) Carcass measurement at 24 months and Genetic Evaluation 2.2 million straw 6

7 Trends in Korean Hanwoo Carcass traits It is very successful!!! ~10kg/10yr ~3cm 2 /10yr ~0.5/10yr 7

8 What is advantages of genomics in Hanwoo breeding? More genetic gain in a short time Reduce generation interval, Increased EBV Effective breeding program Open nucleus system Benefit for New traits to breeding program Low heritability traits Traits that are hard to measure(eg, feed efficient etc) Benefit for reducing inbreeding Own information rather than family information 8

9 Benefits of SNPs in Animal Breeding Phenotypes GEBVs Pedigree Imputation Check/reconstruct pedigree SNPs 9

10 This talk Genetic architecture of carcass traits in Hanwoo Accuracy of Genomic breeding value Requirement of accurate GEBV Effective pop size Num of SNPs Num of ref. pop size 10

11 Distribution of gene effects vs Models 11

12 Genome wide association study to understand the Genetic Architecture of carcass traits Reference population (n=1,012) consisting of steers from progeny testing: Reference pop for GWAS (n=1,012) Sire =118, dam = 995 Steers genotyped with 50K MS, CWT, EMA and BF 12

13 Genome wide association for Carcass weight 13

14 SNP effect (Vg) SNP effect (Vp) 16kg 38kg 356kg 14

15 Back Fat Thickness 15

16 Eye muscle area 16

17 Marbling score 17

18 This talk Genetic architecture of carcass traits in Hanwoo Accuracy of Genomic breeding value Requirement of accurate GEBV Effective pop size Num of SNPs Num of ref. pop size 18

19 19 육종가표현형혈통통계모델 (BLUP) 유전자형 G -1 GBLUP = = = = ) (1 2 ' ) (1 2 ) ( ' ) ( i i a i i u u a p p zz G p p G g Var zz g Var σ σ σ σ

20 Genomic Selection_Prediction of GEBVs Reference pop vs Validation set Reference population (n=1,011) consisting of steers from progeny testing Val set 1 (n=106) consisting of KPN bulls of steers in ref pop Val set 2 (n=178) consisting of progeny without obs Val set 3 (n=236) consisting of Line breeding in Hanwoo station Sire =118, dam = 995 Reference pop (n=1,011) Steers genotyped by 50K IMF, MS, CWT, EMA and BF KPN1 KPN2 KPN3 Progeny tested pop Genomic Prediction GBLUP Val set 1(n=106) Candidate bull for progeny Val set 2(n=178) Progeny without obs Val set 3(n=236) Bull and female for line breeding in Hanwoo station 20

21 Accuracy of GEBV Traits BLUP GBLUP Diff. Sire without obs. (n = 106) EMA 0.71(0.12) 0.72(0.11) 0.01 BF 0.75(0.13) 0.76(0.12) 0.01 MS 0.75(0.13) 0.76(0.12) 0.01 Progeny without obs.(n=178) EMA 0.30(0.03) 0.35(0.04) 0.04 BF 0.32(0.03) 0.37(0.04) 0.06 MS 0.32(0.03) 0.38(0.04) 0.06 Hanwoo station females without obs. (n=236) EMA 0.11(0.08) 0.29(0.07) 0.18 BF 0.11(0.08) 0.30(0.11) 0.19 MS 0.11(0.08) 0.27(0.12)

22 This talk Genetic architecture of carcass traits in Hanwoo Accuracy of Genomic breeding value Requirement of accurate GEBV Effective pop size Num of SNPs Num of ref. pop size 22

23 Linkage disequilibrium vs Effective pop size 23

24 Num of SNPs Num of SNPs that is required to get accurate GEBV 10NeL *Ne : Num of Effective pop. Size, *L : Length of the genome in Morgan Num of SNPs Ne 24

25 Ref. Pop vs Accuracy of GEBV Mike Goddard Equation r = 1 λ /(2N 1+ a + 2 a)*ln( 1+ a 2 a ) a Accuracy Ne h Ne h Ne h Ne h Ne h Ne h Number of Reference Population 25

26 Summary Technically Genomic selection for complex traits w ork well in Dairy cattle and can be used in Hanwoo Very similar breeding scheme Reference population Large reference population (Bulls or Steers) Phenotypes involved in Breeding goal Genotypes (50K or 700K) 26

27 Research Collaboration with EMBRAPA Imputation of whole genome sequence for individual using Key sire group with WGS Development of Bioinformatics system Development of statistical model for GS Pipeline for GS model Optimization of GS model to Breeding program Controlling Inbreeding More genetic Gains Maintain genetic diversity etc. 27